Arrhythmia substrate identification using wideband motion-corrected late gadolinium enhancement magnetic resonance imaging in a swine model of myocardial infarction with taped implantable cardioverter-defibrillators
Bibliographic record
Abstract
Background: Sudden cardiac death is a leading worldwide cause of cardiac mortality and is largely related to ventricular tachycardia (VT) in patients with known myocardial scarring. In these patients, implantable cardioverter-defibrillator (ICD) therapy reduces arrhythmia-related mortality. However, curative procedures such as catheter ablation are used to homogenize regions of scar and remove structural re-entry circuits that cause VT. Objective: In this paper, we conduct a preliminary experiment comparing 2-dimensional (2D) late gadolinium enhancement (LGE) and 3-dimensional (3D) LGE without an ICD with wideband motion-corrected (WB-MOCO) LGE with an ICD in a cohort of infarcted Yorkshire swine. Methods: Animals were imaged after infarct with conventional 2D and 3D LGE without an ICD present and 2D WB-MOCO LGE with an ICD present. Images were analyzed to determine heterogeneous tissue corridor (HTC) count and location, which were compared with circuit exit locations determined using a 12-lead electrocardiogram. Results: We found a statistically significant increase in HTC count with WB-MOCO LGE, but no significant differences in the number of true-positive or false-positive HTCs per subject. Conclusion: WB-MOCO LGE has reduced specificity to physiologically relevant HTCs than conventional 2D or 3D LGE.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".